Identifying sources of heterogeneity for empirically deriving strategic types: A constrained finite-mixture structural-equation methodology

Wayne S. DeSarbo, C. Anthony Di Benedetto, Kamel Jedidi, Michael Song

Research output: Contribution to journalArticle

48 Scopus citations

Abstract

The resource-based view (RBV) of the firm suggests that strategic deployment of capabilities allows strategic business units (SBUs) to exploit distinctive competencies and create sustainable competitive advantage. Following the RBV, we propose a new predictive methodology for deriving typologies of SBUs that accommodates heterogeneity among SBUs with respect to their strategic capabilities, how effectively they are employed, and performance. Statistically, we devise a constrained finite-mixture structural-equation procedure that simultaneously accounts for firm capabilities, performance outcomes, and the relationships between them. The procedure allows for a comprehensive modeling and grouping of entities, and simultaneously provides a diagnosis of the sources of heterogeneity via the flexibility of estimating a series of nested models. Managerially, our proposed methodology is grounded in the strategic type and RBV literature and can capture the effects of environmental and industry-specific factors. Using data obtained from 216 SBUs in the United States for illustration, the results show that our derived four mixed-type solution dominates the four-group, Prospectors-Analyzers-Defenders-Reactors classification as well as a number of other nested model solutions in terms of objective statistical fit criteria for this data set, suggesting a more contingency-driven strategic stance adopted by these SBUs. We conclude with a discussion of the theoretical and managerial benefits of an improved methodology for empirically deriving strategic typologies.

Original languageEnglish (US)
Pages (from-to)909-924
Number of pages16
JournalManagement Science
Volume52
Issue number6
DOIs
StatePublished - Jun 1 2006

All Science Journal Classification (ASJC) codes

  • Strategy and Management
  • Management Science and Operations Research

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